The present invention relates to the field of information searching. Specifically, the present invention relates to efficient searching of information of networks such as the World Wide Web.
With the advent of the Internet and the Web, the amount of information available grows daily. However, having too much information at one's fingertips does not always mean high quality information, in fact, it may often prevent a decision maker from making sound decisions, by degrading the quality of the decision. Helping decision makers to locate relevant information in an efficient manner is very important both to the person and to an organization in terms of time, cost, data quality and risk management.
Although search engines assist users in finding information, many of the results are irrelevant to the decision problem. This is due in part, to the keyword search approach, which does not capture the user's intent, what we call meta-knowledge. Another reason for irrelevant results from search engines is a “semantic gap” between the meanings of terms used by the user and those recognized by the search engines. In addition, each search engine has its own proprietary and uncustomizable ranking system, where users may not specify search and ranking preferences to a search engine. For example, a shopping agent may go for the lowest price, while the user might want the “most flexible return policy.” Finally, most search engines lack learning capabilities to adapt and personalize user preferences. They may not track large numbers of users. What is needed is a personal agent approach that may help to solve these problems.